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Record W2164572253 · doi:10.1155/2013/562763

Associates of an Elevated Natriuretic Peptide Level in Stable Heart Failure Patients: Implications for Targeted Management

2013· article· en· W2164572253 on OpenAlexaff
Aftab Jan, Ian Dawkins, Niamh Murphy, Patrick Collier, John A. Baugh, Mark Ledwidge, Kenneth McDonald, Chris Watson

Bibliographic record

VenueThe Scientific World JOURNAL · 2013
Typearticle
Languageen
FieldMedicine
TopicHeart Failure Treatment and Management
Canadian institutionsSt. Michael's Hospital
Fundersnot available
KeywordsNatriuretic peptideHeart failureMedicineEjection fractionInternal medicineCardiologyCreatininePopulationBrain natriuretic peptide

Abstract

fetched live from OpenAlex

BACKGROUND: Persistently elevated natriuretic peptide (NP) levels in heart failure (HF) patients are associated with impaired prognosis. Recent work suggests that NP-guided therapy can improve outcome, but the mechanisms behind an elevated BNP remain unclear. Among the potential stimuli for NP in clinically stable patients are persistent occult fluid overload, wall stress, inflammation, fibrosis, and ischemia. The purpose of this study was to identify associates of B-type natriuretic peptide (BNP) in a stable HF population. METHODS: In a prospective observational study of 179 stable HF patients, the association between BNP and markers of collagen metabolism, inflammation, and Doppler-echocardiographic parameters including left ventricular ejection fraction (LVEF), left atrial volume index (LAVI), and E/e prime (E/e') was measured. RESULTS: Univariable associates of elevated BNP were age, LVEF, LAVI, E/e', creatinine, and markers of collagen turnover. In a multiple linear regression model, age, creatinine, and LVEF remained significant associates of BNP. E/e' and markers of collagen turnover had a persistent impact on BNP independent of these covariates. CONCLUSION: Multiple variables are associated with persistently elevated BNP levels in stable HF patients. Clarification of the relative importance of NP stimuli may help refine NP-guided therapy, potentially improving outcome for this at-risk population.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.747
Threshold uncertainty score0.398

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.274
Teacher spread0.251 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2013
Admission routes1
Has abstractyes

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Same venueThe Scientific World JOURNALSame topicHeart Failure Treatment and ManagementFrench-language works237,207